Image-Based Debris Detector with a Circular Channel for Lube Oil High-Throughput Monitoring

Image-based debris sensors are crucial for wear monitoring, but the narrow flow channel under oil debris microimaging conditions hinders high-throughput monitoring due to increased flow resistance and susceptibility to clogging. And a large-diameter image-based debris sensor was proposed. The sensor uses a rotationally symmetric high-gradient magnetic field (HGMF) to deposit wear debris on the inner wall of the circular channel. The resulting debris images exhibit local defocus blur. An automatic labeling dataset of the local defocus blur debris images (LDBDIs) was constructed, and a denoising diffusion probabilistic model (DDPM) was used to achieve high-quality restoration of the LDBDIs and to extend the depth-of-field (DOF) of wear debris microimaging on the cylindrical surface. The proposed sensor realizes large depth-of-field imaging of wear debris under a high flow rate and can provide a new solution for the online monitoring of equipment wear.